Literature DB >> 27587048

The effectiveness of pretreatment physics plan review for detecting errors in radiation therapy.

Olga Gopan1, Jing Zeng1, Avrey Novak1, Matthew Nyflot1, Eric Ford1.   

Abstract

PURPOSE: The pretreatment physics plan review is a standard tool for ensuring treatment quality. Studies have shown that the majority of errors in radiation oncology originate in treatment planning, which underscores the importance of the pretreatment physics plan review. This quality assurance measure is fundamentally important and central to the safety of patients and the quality of care that they receive. However, little is known about its effectiveness. The purpose of this study was to analyze reported incidents to quantify the effectiveness of the pretreatment physics plan review with the goal of improving it.
METHODS: This study analyzed 522 potentially severe or critical near-miss events within an institutional incident learning system collected over a three-year period. Of these 522 events, 356 originated at a workflow point that was prior to the pretreatment physics plan review. The remaining 166 events originated after the pretreatment physics plan review and were not considered in the study. The applicable 356 events were classified into one of the three categories: (1) events detected by the pretreatment physics plan review, (2) events not detected but "potentially detectable" by the physics review, and (3) events "not detectable" by the physics review. Potentially detectable events were further classified by which specific checks performed during the pretreatment physics plan review detected or could have detected the event. For these events, the associated specific check was also evaluated as to the possibility of automating that check given current data structures. For comparison, a similar analysis was carried out on 81 events from the international SAFRON radiation oncology incident learning system.
RESULTS: Of the 356 applicable events from the institutional database, 180/356 (51%) were detected or could have been detected by the pretreatment physics plan review. Of these events, 125 actually passed through the physics review; however, only 38% (47/125) were actually detected at the review. Of the 81 events from the SAFRON database, 66/81 (81%) were potentially detectable by the pretreatment physics plan review. From the institutional database, three specific physics checks were particularly effective at detecting events (combined effectiveness of 38%): verifying the isocenter (39/180), verifying DRRs (17/180), and verifying that the plan matched the prescription (12/180). The most effective checks from the SAFRON database were verifying that the plan matched the prescription (13/66) and verifying the field parameters in the record and verify system against those in the plan (23/66). Software-based plan checking systems, if available, would have potential effectiveness of 29% and 64% at detecting events from the institutional and SAFRON databases, respectively.
CONCLUSIONS: Pretreatment physics plan review is a key safety measure and can detect a high percentage of errors. However, the majority of errors that potentially could have been detected were not detected in this study, indicating the need to improve the pretreatment physics plan review performance. Suggestions for improvement include the automation of specific physics checks performed during the pretreatment physics plan review and the standardization of the review process.

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Year:  2016        PMID: 27587048     DOI: 10.1118/1.4961010

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  12 in total

Review 1.  Automated Plan Checking Software Demonstrates Continuous and Sustained Improvements in Safety and Quality: A 3-year Longitudinal Analysis.

Authors:  Delaney Stuhr; Ying Zhou; Hai Pham; Jian-Ping Xiong; Shi Liu; James G Mechalakos; Sean L Berry
Journal:  Pract Radiat Oncol       Date:  2021-10-17

2.  Development of a taxonomy for characterising medical oncology-related patient safety and quality incidents: a novel approach.

Authors:  Joseph O Jacobson; Jessica Ann Zerillo; Therese Mulvey; Sherri O Stuver; Anna C Revette
Journal:  BMJ Open Qual       Date:  2022-07

3.  Strategies for effective physics plan and chart review in radiation therapy: Report of AAPM Task Group 275.

Authors:  Eric Ford; Leigh Conroy; Lei Dong; Luis Fong de Los Santos; Anne Greener; Grace Gwe-Ya Kim; Jennifer Johnson; Perry Johnson; James G Mechalakos; Brian Napolitano; Stephanie Parker; Deborah Schofield; Koren Smith; Ellen Yorke; Michelle Wells
Journal:  Med Phys       Date:  2020-04-15       Impact factor: 4.071

4.  Optimizing efficiency and safety in external beam radiotherapy using automated plan check (APC) tool and six sigma methodology.

Authors:  Shi Liu; Karl K Bush; Julian Bertini; Yabo Fu; Jonathan M Lewis; Daniel J Pham; Yong Yang; Thomas R Niedermayr; Lawrie Skinner; Lei Xing; Beth M Beadle; Annie Hsu; Nataliya Kovalchuk
Journal:  J Appl Clin Med Phys       Date:  2019-08       Impact factor: 2.102

5.  Computer automation for physics chart check should be adopted in clinic to replace manual chart checking for radiotherapy.

Authors:  Edward L Clouser; Quan Chen; Yi Rong
Journal:  J Appl Clin Med Phys       Date:  2021-02-02       Impact factor: 2.102

6.  Toward automation of initial chart check for photon/electron EBRT: the clinical implementation of new AAPM task group reports and automation techniques.

Authors:  Huijun Xu; Baoshe Zhang; Mariana Guerrero; Sung-Woo Lee; Narottam Lamichhane; Shifeng Chen; Byongyong Yi
Journal:  J Appl Clin Med Phys       Date:  2021-03-11       Impact factor: 2.102

7.  Automatic Verification of Beam Apertures for Cervical Cancer Radiation Therapy.

Authors:  Kelly Kisling; Carlos Cardenas; Brian M Anderson; Lifei Zhang; Anuja Jhingran; Hannah Simonds; Peter Balter; Rebecca M Howell; Kathleen Schmeler; Beth M Beadle; Laurence Court
Journal:  Pract Radiat Oncol       Date:  2020-05-23

8.  Failure mode and effect analysis for linear accelerator-based paraspinal stereotactic body radiotherapy.

Authors:  Sangkyu Lee; Dale Michael Lovelock; Alex Kowalski; Kate Chapman; Robert Foley; Mary Gil; Gerri Pastrana; Daniel S Higginson; Yoshiya Yamada; Lei Zhang; James Mechalakos; Ellen Yorke
Journal:  J Appl Clin Med Phys       Date:  2021-10-28       Impact factor: 2.102

Review 9.  Barriers and facilitators to clinical implementation of radiotherapy treatment planning automation: A survey study of medical dosimetrists.

Authors:  Rachel Petragallo; Naomi Bardach; Ezequiel Ramirez; James M Lamb
Journal:  J Appl Clin Med Phys       Date:  2022-03-03       Impact factor: 2.243

10.  Efficiency and safety increases after the implementation of a multi-institutional automated plan check tool at our institution.

Authors:  Sean L Berry; Ying Zhou; Hai Pham; Sharif Elguindi; James G Mechalakos; Margie Hunt
Journal:  J Appl Clin Med Phys       Date:  2020-03-20       Impact factor: 2.102

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